# -*- coding: utf-8 -*-
from datetime import timedelta
from utils.operators.cluster_for_spark_sql_operator import SparkSqlOperator
from jms_data_back_up.dwd.dataplat.dwd_bgdm_fsimage_info_split import jms_dwd__dwd_bgdm_fsimage_info_split
jms_dwd__dwd_bgdm_fsimage_info_split_rk = SparkSqlOperator(
    task_id='jms_dwd__dwd_bgdm_fsimage_info_split_rk',
    task_concurrency=1,
    pool_slots=2,
    master='yarn',
    execution_timeout=timedelta(minutes=30),
    email=['payne.jiang@jtexpress.com','yl_bigdata@yl-scm.com'],
    name='jms_dwd__dwd_bgdm_fsimage_info_split_rk_{{ execution_date | date_add(1) | cst_ds }}',
    sql='jms_data_back_up/dwd/dataplat/dwd_bgdm_fsimage_info_split_rk/execute.sql',
    executor_cores=4,
    executor_memory='8G',
    num_executors=10,
    conf={
        'spark.dynamicAllocation.enabled': 'true',  # 动态资源开启
        'spark.shuffle.service.enabled': 'true',  # 动态资源 Shuffle 服务开启
        'spark.dynamicAllocation.maxExecutors': 20,  # 动态资源最大扩容 Executor 数
        'spark.dynamicAllocation.cachedExecutorIdleTimeout': 30,  # 动态资源自动释放闲置 Executor 的超时时间(s)
        'spark.executor.memoryOverhead': '2G',  # 堆外内存
        'spark.hadoop.hive.exec.dynamic.partition.mode': 'nonstrict', # 动态分区
        'spark.hadoop.hive.exec.dynamic.partition': 'true',
        'spark.sql.shuffle.partitions': 200
    },
    # hiveconf={'hive.exec.dynamic.partition': 'true',
    #           'hive.exec.dynamic.partition.mode': 'nonstrict',
    #           'hive.exec.max.dynamic.partitions.pernode': 200,
    #           'hive.exec.max.dynamic.partitions': 200
    #           },
    yarn_queue='pro',
)

jms_dwd__dwd_bgdm_fsimage_info_split_rk << jms_dwd__dwd_bgdm_fsimage_info_split